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Artificial Neural Network (ANN) for Prediction of Viscosity Reduction of Heavy Crude Oil using Different Organic Solvents
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The increase globally fossil fuel consumption as it represents the main source of energy around the world, and the sources of heavy oil more than light, different techniques were used to reduce the viscosity and increase mobility of heavy crude oil. this study focusing on the experimental tests  and modeling with Back Feed Forward Artificial Neural Network (BFF-ANN) of the dilution technique to reduce a  heavy oil viscosity that was collected from the south- Iraq oil fields using organic solvents, organic diluents with different weight percentage  (5, 10 and  20 wt.% )  of  (n-heptane, toluene, and a mixture of  different ratio toluene / n-Heptane)  at constant temperature. Experimentally the higher viscosity reduction was about from 135.6 to 26.33 cP when the mixture of toluene/heptane (75/25 vol. %) was added. The input parameters for the model were solvent type, wt. % of solvent, RPM and shear rate, the results have been demonstrated that the proposed model has superior performance, where the obtained value of R was greater than 0.99 which confirms a good agreement between the correlation and experimental data, the predicate for reduced viscosity and DVR was with accuracy 98.7%, on the other hand, the μ and DVR% factors were closer to unity for the ANN model.

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Publication Date
Tue Mar 22 2016
Journal Name
Offshore Technology Conference Asia
Nanofluids for Enhanced Oil Recovery Processes: Wettability Alteration Using Zirconium Oxide
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Ultimate oil recovery and displacement efficiency at the pore-scale are controlled by the rock wettability thus there is a growing interest in the wetting behaviour of reservoir rocks as production from fractured oil-wet or mixed-wet limestone formations have remained a key challenge. Conventional waterflooding methods are inefficient in such formation due to poor spontaneous imbibition of water into the oil-wet rock capillaries. However, altering the wettability to water-wet could yield recovery of significant amounts of additional oil thus this study investigates the influence of nanoparticles on wettability alteration. The efficiency of various formulated zirconium-oxide (ZrO2) based nanofluids at different nanoparticle concentrations (0

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Publication Date
Thu Mar 01 2007
Journal Name
Al-khwarizmi Engineering Journal
The Inverse Solution Of Dexterous Robot By Using Neural Networks
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The inverse kinematics of redundant manipulators has infinite solutions by using conventional methods, so that, this work presents applicability of intelligent tool (artificial neural network ANN) for finding one desired solution from these solutions. The inverse analysis and trajectory planning of a three link redundant planar robot have been studied in this work using a proposed dual neural networks model (DNNM), which shows a predictable time decreasing in the training session. The effect of the number of the training sets on the DNNM output and the number of NN layers have been studied. Several trajectories have been implemented using point to point trajectory planning algorithm with DNNM and the result shows good accuracy of the end

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Publication Date
Wed Jun 30 2010
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Producing Oil from Dead Oil Wells Using injected LPG
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In order to reduce hydrostatic pressure in oil wells and produce oil from dead oil wells, laboratory rig was constructed, by injecting LPG through pipe containing mixture of two to one part of East Baghdad crude oil and water. The used pressure of injection was 2.0 bar, which results the hydrostatic pressure reduction around 246 to 222 mbar and flow rate of 34.5 liter/hr fluid (oil-water), at 220 cm injection depth. Effects of other operating parameters were also studied on the behavior of two phase flow and on the production of oil from dead oil wells.

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Publication Date
Sun Jun 04 2017
Journal Name
Baghdad Science Journal
Estimating of Fatty Acids, Tcopherols, Tocotrienols, Total Carotens, Study The Physiochemical Properties And Unsaponifiable Matters Extraction From Crude Red Palm Oil(1)
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The percentage of fatty acids, quantity of tocopherols, tocotrienols, carotens and physiochemical characteristics of crude red palm oil have been evaluated, in addition to specific chemical detection of active compounds unsaponifiable matters. Results of Gas Liquid Chromatography showed:- The major fatty acids in red palm oil is palmitic (44.36%) then oleic (39.65%), linolenic (10.55%), stearic (3.56%), myristic (1.22%), arachdonic (0.24%) and palmotic (0.19%). Red palm oil contains ? – ?- ?- ? – Tocopherols with concentration 258 , 121 , 259, 109 m/kg oil , ? – ?- ?- ? – Tocotrienol with concentration 462.77 , 571.03, 619.18, 509.07 m/kg oil respectively. Total tocopherols & tocotrienols 2909.05 m/kg oil and

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Publication Date
Mon Mar 08 2021
Journal Name
Baghdad Science Journal
Determination of the Ratios of Ligands to Metal Ion of some Metal Complexes of Triazoles by Using Eleetronie Speetra in Organie Solvents
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We found that 4,5- diphenyl- 3(2- propynyl) thio- 1??-triazole [1? forms a complex with Pd (11) ion of ratio 1:1 which absorbs light in CH2CI2 at 400 nm, and 4,5- diphenyl- 3(2- propenyl) thio- 1,2,4- triazole [II] forms complexes with Pd (II) ion of ratio 1:1 which absorbs light at 390 nm, and of ratio 2:1 which absorbs light at 435 nm. On the other hand, we found that the new derivative 4- phenyl- 5( p- amino phenyl) -3- mercapto- 1,2,4- triazole ?111? forms complexes with Cu (II) ion of the ratio 1:1 which absorbs light at 380 nm, with Ni (II) ion of the ratio 3:1 which absorbs light at 358 nm; and with Co (11) ion of the ratio 3.2:1 which absorbs light at 588 nm. The ratio of the complexes were determined by measuring the electronic spe

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Publication Date
Tue Dec 15 2015
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
Determination of some Optimum Conditions for Bioremediation of Some Heavy Metals by Saccharomyces cerevisiae: Determination of some Optimum Conditions for Bioremediation of Some Heavy Metals by Saccharomyces cerevisiae
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The study aimed to determine of some Optimum conditions for bioremediation and removing of seven mineral elements included hexavalent chromium, nickel, cobalt, cadmium, lead, iron and copper as either alone or in group by living and heat treated cells of baker’s yeast Saccharomyces cerevisiae. The dried baker's yeast from Aldnaamaya China Company was used in this study. Biochemical tests was used to ensure yeast belonging to S. cerevisiae and then used to remove the mentioned mineral elementes under different conditions which included incubation period, pH, and temperature. It was found that the best of these conditions was 60 minutes for duration of incubation, 6 for pH, 25 ᵒC for temperature. During the study the behavior of living

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Colloid And Interface Science
Removal of monoethylene glycol from wastewater by using Zr-metal organic frameworks
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Publication Date
Mon Nov 11 2019
Journal Name
Spe
Modeling Rate of Penetration using Artificial Intelligent System and Multiple Regression Analysis
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Abstract<p>Over the years, the prediction of penetration rate (ROP) has played a key rule for drilling engineers due it is effect on the optimization of various parameters that related to substantial cost saving. Many researchers have continually worked to optimize penetration rate. A major issue with most published studies is that there is no simple model currently available to guarantee the ROP prediction.</p><p>The main objective of this study is to further improve ROP prediction using two predictive methods, multiple regression analysis (MRA) and artificial neural networks (ANNs). A field case in SE Iraq was conducted to predict the ROP from a large number of parame</p> ... Show More
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Publication Date
Sat Aug 27 2022
Journal Name
Egyptian Journal Of Chemistry
Evaluation of Zinc Chelation Ability for Non-Hydroxamic Organic Moieties
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Publication Date
Tue Aug 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Prediction of Biodegradability Possibility for Sewage of the Dairy Industry
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he dairy industry is one of the industrial activities classified within the food industries in all phases of the dairy industry, which leads to an increase in the amount of wastewater discharged from this industry. The study was conducted in the Abu Ghraib dairy factory, classified as one of the central factories in Iraq, located in the west of Baghdad governorate, with a design capacity of 22,815 tons of dairy products. The characteristics of the liquid waste generated from the factory were determined for the following parameters biological oxygen demand (BOD5), Chemical oxygen demand (COD), total suspended solids (TSS), pH, nitrate, phosphate, chloride, and sulfate with an average value of (1079, 1945, 323, 9.2, 24, 2

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